Shahab Hasan, Principal Investigator Rosa Oseguera-Lohr, NASA Langley, Technical Monitor Dou Long, George Hart Mike Graham, Terry Thompson, Charles Murphy January 28, 2010 Integrated Analysis of Airport Integrated Analysis of Airport Capacity and Environmental Capacity and Environmental Constraints Constraints
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Shahab Hasan, Principal Investigator Rosa Oseguera-Lohr, NASA Langley, Technical Monitor Dou Long, George Hart Mike Graham, Terry Thompson, Charles Murphy.
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Shahab Hasan, Principal Investigator Rosa Oseguera-Lohr, NASA Langley, Technical Monitor
Dou Long, George HartMike Graham, Terry Thompson, Charles Murphy
January 28, 2010
Integrated Analysis of Airport Capacity and Integrated Analysis of Airport Capacity and Environmental ConstraintsEnvironmental Constraints
P A G E 2
Task Objective
• Identify and rank key factors limiting the achievement of NextGen goals
• Identify capabilities required and gaps in available tools for conducting system-level trade and benefit studies
• Results will help prioritize NASA’s research to enable NextGen
P A G E 3
Overview of Subtasks
3. Develop List of Critical Airports
1. Develop Scenarios
2. Develop Metrics
4. Analyze Airportal Capacity Constraints
5. Analyze Airportal Environmental Constraints
Runway Constraints
Taxiway Constraints
Gates Constraints
Fuel Constraints
Emissions Constraints
Noise Constraints
P A G E 4
Overview of Subtasks 1 - 3• Subtask 1: Develop Set of Scenarios
– 2015 and 2025 flight schedules, generated by FAA, used by JPDO
– NextGen capacities developed and used by JPDO
• Subtask 2: Develop Set of Metrics – Throughput is our primary metric
– Delay is also used for assessing the robustness of future operations
• Subtask 3: Develop Set of Critical Airports – 110 large airports with capacities used in prior LMI analyses plus 200
additional airports with capacities developed by the team • The next largest airports from NPIAS with consideration of infrastructure,
location relative to major metropolitan area or airport, and traffic mix
– Total of 310 airports
– 98.6% of air carrier operations, 99.8% of air carrier enplanements
• We assume no change to the airport capacities at the smaller 200 airports– Likely cost prohibitive for NextGen deployment
• For the 110 larger airports, their capacities can be increased by– New runways– NextGen technologies
• One primary airport runway configuration for each meteorological operating condition
• Airport runway configurations based on analysis of FACT2 and FAA configurations, airport diagrams, capacity data, procedure charts, and knowledge from prior tasks
• Three-pronged approach for taxiway constraint analysis:
1. Airport Elimination – establish a conservative lower bound for taxi capacities at 310 critical airports
• It is very difficult to determine the exact taxiway capacity for a given airport – by establishing a lower bound for taxiway capacity and comparing it to peak demand, we can determine with confidence whether the airport will be taxi-constrained
2. Configuration Analysis – determine if airports are unlikely to have taxi capacity shortages based on their layout and configuration
• Taxi capacity can be determined not to be a constraint if the airport is laid out or operated in such a way that runway/taxiway interaction is minimal
3. Event simulation models at most of the OEP 35 airports
• Simulation is well-suited to modeling the complex surface interactions between aircraft, however building simulations for all 310 airports would be too time consuming for this task
• Taxiway delay is believed to be caused by interaction between the taxiways and the runways
• Therefore, if an airport consistently operates under a configuration (at least 60% of the time) that does not include this interaction, taxiway delay at the airport will be minimal
• We used airport configuration data from the FAA’s 2004 Airport Capacity Benchmark study and from ASPM (limited to the 77 airports covered by ASPM)
• All of the OEP 35 airports were either eliminated using this approach or simulated explicitly (Approach 3, next slide)
• LMI developed a new, Java-based model to model gate capacity and demand
• Model execution time is less than 10 minutes
• Calculate each airport’s gate availability over time using– Gate Capacity: the airport’s total number of gates– Gate Demand: a schedule of arrivals and departures of aircraft
requiring gate access– Reference Point: a known number of aircraft at the gates at some
point in time
• The model focuses on gates with passenger bridges
• The model analyzes all 310 airports, identifies those that are gate constrained, and determines what percentage of flights that would need to be trimmed in order for the airport to remain under capacity
• For the level 2 modeling we developed lower fidelity terminal areas based on runway configuration and weather data for all 310 airports.
• For the level 3 modeling we developed higher fidelity radar driven terminal areas inputs for the FACT 56 airports.– Used two sources (ATA-LAB or PDARS) – Updates to the OEP Airports
Similar tables are created for each of the 310 critical airports for both years
P A G E 27
Constraints for the Busiest 10 Airports, 2025
-
5,000
10,000
15,000
20,000
25,000
30,000
35,000
Unconstrained Runway Taxi Gate Noise Fuel Nox
Op
era
tio
ns
100%
89%
94%
91% 90%
97%
92%
P A G E 28
Constraints for LMI 310 Airports, 2025
-
20,000
40,000
60,000
80,000
100,000
120,000
140,000
160,000
180,000
Unconstrained Runway Taxi Gate Noise Fuel NOx
Da
ily O
pe
rati
on
s
100%
92%93%87%
96%99%
96%
P A G E 29
Constrained Airports in 2025
Table Error! No text of specified style in document.-1. Number of Constrained Airports by Category in 2025
Airport Group Constrained Runway Taxi Gate Fuel NOx Noise
Primary 3 1 1 0 1 3
Secondary 0 1 1 1 4 4 Busiest10
Total 6 6 9 10 10 10
Primary 4 2 4 3 3 19
Secondary 4 1 0 5 17 7 OEP35
Total 21 12 27 35 34 35
Primary 5 2 7 21 18 63
Secondary 5 1 7 34 58 9 LMI110
Total 28 12 79 110 109 103
Primary 5 2 13 111 76 132
Secondary 6 1 10 106 149 18 LMI310
Total 32 12 95 303 305 237
P A G E 30
Conclusions
• Even with full NextGen implementation, some constraints will still exist at some airports– The overall system projected throughput will be no more than
the worst constrained case, losing about 15% of total operations in 2025 (310 airport case under noise)
– Runway constraints are more binding for the largest airports (top 10), losing about 11% operations
– Environmental constraints are widespread and noise is most binding• The environmental goals are quite aggressive and directly affect
the results of this study
P A G E 31
Caveats and Limitations
• Decomposing the system constraints is an analytical technique; we recognize that in the real world, everything is interconnected and mostly inseparable
• Demand forecasts are ever-changing and never perfect; the analysis necessarily is a snapshot
• Capacity estimates are analytically rigorous and our assumptions are reasonable and clearly documented; however, fully successful and timely R&D and implementation of capacity enhancements is an optimistic assumption
• The projected throughput metric, while very useful, models an extreme response (flight trimming) and, in this analysis, we did not model other likely operator responses such as schedule smoothing and use of secondary airports